91 citations · 215 across the 24 of their papers we have counts for
16 papers · 1 filter
FCM-RDpA: TSK Fuzzy Regression Model Construction Using Fuzzy C-Means Clustering, Regularization, DropRule, and Powerball AdaBelief
Zhenhua Shi, Dongrui Wu, Chenfeng Guo +3
To effectively optimize Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a mini-batch gradient descent with regularization, DropRule, and AdaBound (MBGD-RDA) algorit…
A Survey on Negative Transfer
Wen Zhang, Lingfei Deng, Lei Zhang +1
Transfer learning (TL) utilizes data or knowledge from one or more source domains to facilitate the learning in a target domain. It is particularly useful when the target domain ha…
Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline
Dongrui Wu, Xue Jiang, Ruimin Peng +3
Transfer learning (TL) has been widely used in motor imagery (MI) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promis…
Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs
Xiao Zhang, Haoyi Xiong, Dongrui Wu
Over-parameterized deep neural networks (DNNs) with sufficient capacity to memorize random noise can achieve excellent generalization performance, challenging the bias-variance tra…
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016
Dongrui Wu, Yifan Xu, Bao-Liang Lu
A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common non-invasive BCI modality, electroencephalogram (EEG),…
Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)
Ziang Liu, Xue Jiang, Hanbin Luo +3
Active learning (AL) selects the most beneficial unlabeled samples to label, and hence a better machine learning model can be trained from the same number of labeled samples. Most…